The AI in Business Podcast

As financial institutions move beyond AI experimentation, the primary bottleneck is no longer capability; it is governance. In this episode, Yoav Naveh, Co-Founder and Co-CEO at Reindeer AI, examines how enterprises can operationalize agentic AI inside regulated financial workflows, including the two-loop oversight model that keeps agents compliant, self-correcting, and continuously improving. The conversation covers what it means for agents to self-heal when they encounter exceptions, how decision logic should be governed in practice, and how to approach the build-versus-buy decision in a way that places accountability ahead of capability.


This episode is sponsored by Reindeer AI. In this episode, we cover how enterprises in banking and financial services are operationalizing agentic AI inside regulated workflows — and what governance infrastructure actually makes it sustainable at scale.


To go deeper on this topic and learn how banks are using RPA to reduce operational costs in repetitive workflows and applying anomaly detection to identify fraud in real time, download our free PDF report, "AI in Banking Executive Cheat Sheet," at emerj.com/bcs1

Enterprise AI adoption is moving faster than security and governance frameworks can follow,  forcing organizations to make difficult trade-offs between competitive urgency and operational risk. In this episode, Jason Loomis, CISO at Freshworks, examines why most enterprises have not yet resolved the tension between AI deployment speed and security maturity, and outlines a sequenced approach; beginning with regulatory compliance, advancing through data trust, and extending into AI-specific security frameworks. The conversation covers how leadership can build the investment case for AI, how culture shapes adoption outcomes, and why the biggest executive mistake is expecting returns before committing the resources that make them possible. Connect with ideal enterprise AI through the strategies Emerj employs to help leading AI brands and startups: emerj.com/AD1

As enterprises move from single to multi-agent AI deployments, a coordination infrastructure problem is emerging that connectivity protocols alone cannot solve. In this episode, Guillaume de Saint Marc, VP of Engineering at Outshift, examines why agents that can communicate still fail to collaborate — and outlines the semantic alignment, shared memory, and authorization architecture required to address it. The discussion covers specific failure modes in production multi-agent systems, the organizational security and observability decisions that determine whether agentic deployments scale, and how open standards protect enterprises from vendor lock-in as the space evolves.
 
This episode is sponsored by Outshift by Cisco. In this episode, we cover why enterprises scaling multi-agent AI need more than connected agents — they need shared semantic grounding, persistent memory, and fine-grained authorization to enable genuine collaboration. To go deeper on this topic and learn how consultants are winning business with evidence-based AI ROI, and building long-term capabilities instead of chasing short-term gains, download our free PDF report, "3 Keys to Thriving in the Coming Era of Automation" at emerj.com/cok1

A widening gap between mature digital compute and the newly awakening physical world is forcing enterprises to rethink how they embed AI into logistics, manufacturing, and other high‑stakes environments where errors carry real operational risk.


In this episode, Drew Henry, Executive Vice President for Physical AI at Arm, joins host Daniel Faggella and examines how leaders are navigating the shift from fixed automation to model‑driven intelligent control, and what it takes to make confident, high‑impact infrastructure decisions amid rapid algorithmic and hardware change.


The discussion highlights how advanced teams ground adoption in concrete operational problems, build competency around new model‑based interfaces, and use simulation and digital twins to de‑risk retooling in power‑ and compute‑constrained environments.


If you want to listen to the same things that other infrastructure and AI leaders in the Fortune 500 are tuned into, then check out the AI infrastructure podcast, it's emerj.com/inf1

A surge in AI adoption is creating a rights gap inside financial institutions, where everyday workflows now generate copyrighted reproductions at a scale existing governance models were never built to manage. In this episode, Roanie Levy, Licensing and Legal Advisor at CCC, joins host Yolandi de Weerdt and examines how AI‑driven content use is outpacing traditional licensing frameworks and why leaders must verify rights before embedding copyrighted material into AI systems. The discussion highlights the operational decisions executives need to make around content governance, rights validation, and cross‑functional controls to prevent downstream legal and workflow disruption. This episode is sponsored by CCC. If you offer AI products or services into the enterprise, you need to find enterprise leaders with relevance and readiness.
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To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1